# Labelbox vs Scalebrowser

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. Scalebrowser records 161,955 monthly visits with +212.7% growth and Free Trial, Paid pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [Scalebrowser](https://openaitools.app/tool/scalebrowser) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://scalebrowser.net |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI Browsers, AI Agent, AI Developer Tools, AI API |
| Pricing Model | Contact for Pricing | Free Trial, Paid |
| Monthly Visits | 762,803 | 161,955 |
| MoM Growth Rate | -22.8% | +212.7% |
| Primary Market | United States | Global |
| Direct Visits | 370,024 | 65,234 |
| Review Score | 4.4 | 4.7 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Labelbox

Labelbox occupies an unusual position in the AI stack: it does not primarily sell a chatbot or a generator, it builds the environments and data that models learn from plus the agents that take over recurring engineering and research work. The homepage claim is direct — frontier AI labs train on Labelbox environments and expert data, while engineering and research teams hand their recurring backlog to agents running on Recursion. A recent Series E of more than $100 million signals a heavily funded bet on that thesis.,For enterprises, the newer half of the product is Recursion. Agents are triggered by real signals — a failing build, a PagerDuty alert, a new dependency release, a fresh model checkpoint, or a Monday morning schedule — and then work in the background until the job is done. The examples the company promotes are concrete deliverables rather than summaries: a tested pull request with a preview link, a postmortem draft in Confluence with every event sourced, an ablation table naming the changes that mattered, or a patch for each exposed service after a critical CVE. A grader agent scores each run, and the graded session leaves behind memories, notes and skills that the next session reads before it acts.,The original foundation remains the data business: labeling, annotation, curation and model evaluation supported by expert human reviewers, used for computer vision, NLP, supervised fine-tuning, RLHF and red teaming. In practice the two halves reinforce each other, since the environments that produce high-quality training data are the same environments where agents learn to do real work. Pricing is enterprise-style, routed through sales conversations and shaped by data volume and agent usage, with no public self-serve tier.

**Pricing & Plans:** Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases.

- **Data labeling and expert annotation:** Structured annotation, curation, model evaluation and human-in-the-loop review across vision, language and generative tasks, used to build the training and eval data behind production models.
- **Autonomous agent sessions:** Recursion agents start on their own from builds, alerts, commits, checkpoints and schedules, then work in the background until the task is finished and reviewable.
- **Domain specialists by function:** Specialist agents cover software engineering, reliability, security, ML research, evals, R&D, product and finance workflows, from flaky test fixes to postmortem drafts and vulnerability patches.
- **Graded outcomes that compound:** Every agent run is scored by a grader, and graded sessions leave memories, notes and skills that the next session reads before acting, so quality compounds over time.
- **Native tool and data integrations:** Agents operate against the tools teams already use, including GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery, Databricks, Vercel and cloud providers.

**Strengths:** Covers both sides of the problem: training and eval data production plus agents that act on recurring work; Backed by a recent $100M+ Series E and adoption by frontier AI labs, indicating real funding and demand; Agent runs produce concrete deliverables with proof — tests, reruns, ablations — rather than unverified suggestions; Integrates with the toolchain teams already run: GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery and Databricks

**Limitations:** No self-serve pricing or open signup: everything routes through a sales conversation, which slows down evaluation; The platform assumes real engineering and research infrastructure (GitHub, cloud providers, data warehouses) to deliver value; Positioning has shifted quickly toward autonomous agent sessions, so teams wanting only labeling workflows may find it heavier than needed

[Profile (Markdown)](https://openaitools.app/tool/labelbox.md)

## Scalebrowser

>Scalebrowser targets the part of agent work that usually breaks first: staying authenticated. Instead of scraping a signed-out page or re-logging in on every run, it hands each agent a browser machine that keeps a stable identity, complete with stored passwords, per-profile inboxes, two-factor codes and passkeys. The product installs as a desktop app so the GPU, screen and fingerprint values match the real machine, which reduces the chance that a profile contradicts itself.

On top of the browser layer, Scalebrowser adds an agent layer. Agents read a page once and then only what changed, which keeps token spend predictable on long runs. Captchas are handled through human-like input, keys on a page are surfaced to the agent as placeholders, and each tool call is logged as a step with a result and a screenshot. It works with MCP clients such as Claude and Cursor, Python and Node SDKs, a REST API and direct CDP for existing browser-use code.

Plans are measured by how much runs at once. The free tier covers a single browser and three profiles, while paid tiers grow concurrent browsers, machines, profiles and workflows. Workflows can be started by hand or by an agent, and higher tiers add schedules, webhooks, sync and phone approvals.

**Pricing & Plans:** Free plan with 1 concurrent browser, 1 machine and 3 profiles, no card required. Paid plans: Start at $19/month (1 browser, 25 profiles), Solo at $49/month (5 browsers, 100 profiles), Studio at $99/month (20 browsers, 3 machines, 500 profiles), and custom Enterprise pricing. Most paid plans include a 7-day free trial.

- **Persistent profile identity:** Each profile is generated from a seed so its identity, cookies and logins persist across restarts, and sites see the same returning visitor rather than a new device.
- **Isolated browser profiles:** One browser per profile means separate logins, cookies and devices that share nothing, making multi-account automation safe to run in parallel.
- **Built-in sign-in and 2FA handling:** Agents get through username and password forms, email confirmation codes, TOTP and SMS two-factor codes, passkeys and permission prompts without stalling.
- **Human-like input and captchas:** Press-and-hold, image grid, slider and rotation captchas are solved through human-like input rather than third-party solving keys.
- **Flexible agent integrations and trails:** Connect over MCP, Python or Node SDKs, REST or direct CDP, and review every action as a step with its result and screenshot.

**Strengths:** Strong focus on persistent, isolated identities so agents stay logged in across runs; Broad integration surface covering MCP, Python/Node SDKs, REST and direct CDP; Built-in handling of logins, email codes, TOTP, SMS, passkeys and captchas; Token-efficient page reading that only reports what changed between steps

**Limitations:** Requires installing a desktop app and running it on your own machine, so it is not a purely cloud-hosted service; Free tier excludes schedules, webhooks, sync and phone approvals; Paid tiers meter concurrent browsers, machines and profile counts, which can raise costs for large fleets; Advanced anti-detection features may raise compliance responsibility with target platforms

[Profile (Markdown)](https://openaitools.app/tool/scalebrowser.md)

## Frequently Asked Questions

### How do Labelbox and Scalebrowser compare in monthly traffic?

Labelbox has 762,803 monthly visits, while Scalebrowser has 161,955. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Labelbox has a month-over-month growth rate of -22.8%; Scalebrowser has +212.7%.

### How does pricing compare?

Labelbox: Contact for Pricing. Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases. Scalebrowser: Free Trial, Paid. Free plan with 1 concurrent browser, 1 machine and 3 profiles, no card required. Paid plans: Start at $19/month (1 browser, 25 profiles), Solo at $49/month (5 browsers, 100 profiles), Studio at $99/month (20 browsers, 3 machines, 500 profiles), and custom Enterprise pricing. Most paid plans include a 7-day free trial.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Apify](https://openaitools.app/tool/apify) | 4,147,762 | +3.9% | Freemium, Contact for Pricing | A massive cloud web scraping and automation marketplace, though it lacks Scalebrowser's focus on persistent isolated profiles. | [.md](https://openaitools.app/tool/apify.md) |
| 2 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines end-to-end computer vision workflows from annotation to model deployment, but lacks Labelbox's general enterprise agent orchestration. | [.md](https://openaitools.app/tool/roboflow.md) |
| 3 | [Appen](https://openaitools.app/tool/appen-com) | 665,840 | +0.2% | Contact for Pricing | Relies heavily on managed human-in-the-loop workforce services for data validation, offering less self-serve technical tooling than Labelbox. | [.md](https://openaitools.app/tool/appen-com.md) |
| 4 | [Scale](https://openaitools.app/tool/scale) | 616,915 | +12.5% | Contact for Pricing | Delivers enterprise-grade labeling and model evaluation at massive scale, but often requires higher enterprise budgets than Labelbox. | [.md](https://openaitools.app/tool/scale.md) |
| 5 | [Eigent AI](https://openaitools.app/tool/eigent-ai) | 575,703 | +1.4% | Freemium, Free Trial, Contact for Pricing | Open-source desktop AI workforce that runs browser, file, and app tasks for you | [.md](https://openaitools.app/tool/eigent-ai.md) |
| 6 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | Offers robust multimodal annotation and workflow automation, featuring slightly more intuitive data curation pipelines for computer vision teams. | [.md](https://openaitools.app/tool/super-annotate.md) |
| 7 | [ego (lite)](https://openaitools.app/tool/ego-lite) | 384,099 | +97.6% | Free | A free Chromium-based browser optimized for running parallel AI web automation and scraping tasks locally. | [.md](https://openaitools.app/tool/ego-lite.md) |
| 8 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |
| 9 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | Specializes in advanced computer vision and physical AI data pipelines, though with a narrower focus than general text-and-image labeling. | [.md](https://openaitools.app/tool/encord-com.md) |
| 10 | [Happycapy](https://openaitools.app/tool/happycapy) | 191,406 | +7.2% | Freemium | An agent-native computer that works while you sleep | [.md](https://openaitools.app/tool/happycapy.md) |

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Source: https://openaitools.app/compare/labelbox-vs-scalebrowser

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)
